Javascript 从neo4j rest API创建json的正确方法
我想创建以下jsonJavascript 从neo4j rest API创建json的正确方法,javascript,neo4j,Javascript,Neo4j,我想创建以下json "model":[ { "_id": 123, "innerMode1": [ { "_id": 233, "_type": "somtype2", "innerMode2": [ { "_id": 24533,
"model":[
{
"_id": 123,
"innerMode1": [
{
"_id": 233,
"_type": "somtype2",
"innerMode2": [
{
"_id": 24533,
"_type": "somtype3",
"innerMode2": [
{ ....this goes on till depth of 6
}
]
}
]
}
], "_id": 45123,
"innerMode2": [
{
"_id": 23433,
"_type": "somtype2",
"innerMode2": [
{
"_id": 241233,
"_type": "somtype3",
"innerMode2": [
{
....this goes on till depth of 6
}
]
}
]
}
]
.
.
.
.
.
1000 records
塞弗说:
MATCH (c:Capability{SectorID:{varSectorID}})-[r1:CapabilityAdopts_Capability]->(d)-[r2:Capability_Capability]->(e)-[r3:Capability_Capability]->(f)
OPTIONAL MATCH (f)<-[r3:Capability_Capability]-(g)
OPTIONAL MATCH (f)-[r4:KPI_Capability]-(h)
RETURN c,labels(c),r1,Type(r1),d,labels(d),r2,Type(r2),e,labels(e),r3,Type(r3),f,labels(f),r4,Type(r4),g,labels(g),r5,Type(r5),h,labels(h)
MATCH(c:Capability{SectorID:{varSectorID})-[r1:CapabilityAdopts_Capability]->(d)-[r2:Capability_Capability]->(e)-[r3:Capability_Capability]->(f)
可选匹配(f)您可以使用collect+map和collection语法创建类似于您在一个cypher语句中描述的内容,您可以从最低级别开始,然后沿着路径向上聚合
不幸的是,我无法理解你的解释
下面是一篇文章的链接,详细解释了这一点:
这正是我想要的。谢谢你的帮助。
var capObjectsContainer= {
model: []
};
var mainContainerL2 = jsonData.results[4].data; //this comes from neo after running the above cypher
for (i = 0; i < mainContainerL2.length; i++) {
var isPartOfCapabilityContainer = {
isPartOfCapability: []
};
var capIsMeasuredByKPIPatternContainer = {
cpbltyIsMsrdByKpiPttrn: []
};
var consistsOfCapContainer = {
consistsOfCapability: []
};
var isconsistsOfCap2Present = false;
for (j = 0; j < capObjectsContainer.model.length; j++) {
if (mainContainerL2[i].row[0]["ExternalID"] == capObjectsContainer.model[j]["_id"]) {
for (k = 0; k < capObjectsContainer.model[j].adoptsCapability.length; k++) {
if (mainContainerL2[i].row[4]["ExternalID"] == capObjectsContainer.model[j].adoptsCapability[k]["_id"]) {
for (l = 0; l < capObjectsContainer.model[j].adoptsCapability[k].consistsOfCapability.length; l++) {
if (mainContainerL2[i].row[8]["ExternalID"] == capObjectsContainer.model[j].adoptsCapability[k].consistsOfCapability[l]["_id"]) {
for (m = 0; m < capObjectsContainer.model[j].adoptsCapability[k].consistsOfCapability[l].consistsOfCapability.length; m++) {
if (mainContainerL2[i].row[12]["ExternalID"] == capObjectsContainer.model[j].adoptsCapability[k].consistsOfCapability[l].consistsOfCapability[m]["_id"]) {
if (mainContainerL2[i].row[20] != null)
AddcapIsMeasuredByKPIPattern(capObjectsContainer.model[j].adoptsCapability[k].consistsOfCapability[l].consistsOfCapability[m].cpbltyIsMsrdByKpiPttrn, mainContainerL2[i].row[20], mainContainerL2[i].row[21])
if (mainContainerL2[i].row[16] != null && !IsExternalIdPresent(capObjectsContainer.model[j].adoptsCapability[k].consistsOfCapability[l].consistsOfCapability[m].isPartOfCapability, mainContainerL2[i].row[16]))
AddIsPartOfCap(capObjectsContainer.model[j].adoptsCapability[k].consistsOfCapability[l].consistsOfCapability[m].isPartOfCapability, mainContainerL2[i].row[16], mainContainerL2[i].row[17])
isconsistsOfCap2Present = true;
break;
}
}
if (!isconsistsOfCap2Present) {
if (mainContainerL2[i].row[20] != null)
AddcapIsMeasuredByKPIPattern(capIsMeasuredByKPIPatternContainer.cpbltyIsMsrdByKpiPttrn, mainContainerL2[i].row[20], mainContainerL2[i].row[21])
if (mainContainerL2[i].row[16] != null)
AddIsPartOfCap(isPartOfCapabilityContainer.isPartOfCapability, mainContainerL2[i].row[16], mainContainerL2[i].row[17])
if (mainContainerL2[i].row[12] != null)
AddConsistsOfCap(capObjectsContainer.model[j].adoptsCapability[k].consistsOfCapability[l].consistsOfCapability, mainContainerL2[i].row[12], mainContainerL2[i].row[13], isPartOfCapabilityContainer.isPartOfCapability, capIsMeasuredByKPIPatternContainer.cpbltyIsMsrdByKpiPttrn, consistsOfCapContainer.consistsOfCapability)
}
break;
}
}
}
}
}
}
}